Causal relationship between multiple sclerosis and spinal stenosis: Two-sample Mendelian randomization

To investigate the causal relationship between multiple sclerosis and spinal stenosis using Mendelian randomization (MR). Genetic loci independently associated with multiple sclerosis and spinal stenosis in people of European origin were selected as instrumental variables using pooled data from genome wide association studies (GWAS). Three MR analyses, MR-Egger, Weighted median and inverse variance weighting (IVW), were used to investigate the causal relationship between multiple sclerosis and spinal stenosis. Heterogeneity and multiplicity tests were performed, and sensitivity analyses were performed using the “leave-one-out” method to explore the robustness of the results. The IVW results showed an OR (95% CI) of 1.05 (1.01–1.08), P = .016, indicating a causal relationship between MS and spinal stenosis. And no heterogeneity and multiplicity were found by the test, and sensitivity analysis also showed robust results. In this study, genetic data were analyzed and explored using 2-sample MR analysis, and the results showed a causal relationship between multiple sclerosis and the occurrence of spinal stenosis.


Introduction
Spinal stenosis is a neurological disorder that manifests itself as a narrowing of the space within the spinal canal, resulting in compression of the nerve roots or spinal cord. [1,2]This disease is common in the elderly, especially those over 50 years of age. [3]Spinal stenosis can affect a patient's quality of life, and in severe cases it can even lead to limited mobility.The causes of spinal stenosis are varied and include degenerative changes, bone spurs, and ligamentous hyperplasia.These factors lead to narrowing of the space within the spinal canal, which compresses the nerve roots or spinal cord. [4,5]Symptoms mainly include low back pain, radiating pain in the lower limbs, sensory abnormalities, and loss of muscle strength. [6,7]evere spinal stenosis may also cause dysfunction in urination and defecation. [8]Multiple sclerosis is a chronic, autoimmune disease that primarily affects the central nervous system. [9,10][13] These symptoms may affect patients' daily activities and quality of life.Some studies have suggested that patients with multiple sclerosis may be more prone to spinal stenosis, but relevant studies are lacking. [14]Therefore, the causal relationship between multiple sclerosis and spinal stenosis still needs further investigation.
The association between multiple sclerosis and spinal stenosis may be influenced to some extent by confounding factors and reverse causality inherent in traditional observational studies. [15]In contrast, Mendelian randomization (MR), a genetic epidemiological method, is a useful tool for assessing the causal role of multiple sclerosis and spinal stenosis. [16]By using genetic variants such as single nucleotide polymorphisms (SNPs) as instrumental variants that can modify disease risk factors or exposures, MR studies can enhance causal inference of exposure-outcome associations. [17]According to Mendel's laws of inheritance, genetic variants are not susceptible to confounding factors because they are randomly assigned during gamete formation. [18]In addition, confounders and reverse causality can be minimized as genotypes cannot change as the disease progresses. [19]o this end, we conducted a 2-sample MR study to examine the causal relationship between multiple sclerosis and spinal stenosis.We aimed to provide significant evidence for the causal role of MS in causing spinal stenosis.

Data sources
The genome wide association studies (GWAS) data for multiple sclerosis and spinal stenosis were obtained via the IEU The authors have no funding and conflicts of interest to disclose.
The datasets generated during and/or analyzed during the current study are publicly available.
OpenGWAS project (mr cieu.ac.uk) website.The website was accessed on 2023-08-06.The population source for all final data was European, male and female.Including multiple sclerosis (ebi-a-GCST005531) containing 132,089 SNPs with a sample size of 38,582, and spinal stenosis (finn-b-M13_SPINSTENOSIS) containing 16,380,277 SNPs with 9169 in the experimental group and 164,682 in the control group.This study was a re-analysis of previously collected and published public data and therefore did not require additional ethical approval.

Conditioning of SNP as an instrumental variable
Instrumental variables were highly correlated with exposure, with F > 10 as a strong correlation criterion. [20]Instrumental variables are not directly correlated with the outcome and only affect the outcome through exposure, i.e. there is no genetic pleiotropy.In this study, the nonexistence of genetic pleiotropy was indicated by the non-zero intercept term of the MR-Egger regression model (P < .05). [21]Instrumental variables were not associated with untested confounding. [22]The human genotypephenotype association database Phenoscanner V2 was searched for phenotypes associated with the instrumental variables at the genome-wide significance level to determine whether these SNPs were associated with potential risk factors. [23]

SNP screening
Significant SNPs were screened from the GWAS pooled data for multiple sclerosis (with P < 5 × 10 −8 as the screening condition) [24] ; the chain imbalance coefficient r 2 was set to 0.001 and the width of the chain imbalance region to 10,000 kb to ensure that individual SNPs were independent of each other. [25]he multiple sclerosis-associated SNPs screened above were extracted from the GWAS pooled data of spinal stenosis, while SNPs directly associated with outcome indicators were excluded (P < 5 × 10 −8 ).The F value of each SNP was calculated, and SNPs with weak instrumental variables (F value < 10) were excluded. [26]And the human genotype-phenotype association database was queried to screen for potentially relevant risk factor SNPs and exclude them. [27]

Causality validation methods
The causal relationship between exposure (multiple sclerosis) and outcome (spinal stenosis) was mainly verified using inverse variance weighted (IVW) as, supplemented by 3 MR analysis methods, MR-Egger and weighted median, with SNPs as instrumental variables.

Sensitivity analysis
Sensitivity analyses were performed using several methods.First, the Cochran Q test was used to assess the heterogeneity between the individual SNP estimates, and a statistically significant Cochran Q test demonstrated significant heterogeneity in the analyses.Second, Mendelian randomization pleiotropy residual sum and outlier (MR PRESSO) was used to validate the results in the IVW model, to correct for the effect of outliers, and if outliers existed, they were removed and the analysis was repeated.Third, the horizontal multiplicity of SNPs was tested using the MR Egger intercept test (MR Egger intercept test), and if the intercept term in the MR Egger intercept test analysis was statistically significant, it indicated that the MR analysis had significant horizontal multiplicity.Fourth, "leave-one-out" sensitivity analyses were performed by removing a single SNP at a time to assess whether the variant drove the association between the exposure and outcome variables.Fifth, funnel plots and forest plots were constructed to visualize the results of the sensitivity analyses.P < .05suggests that there is a potential causal relationship in the MR analyses, which is statistically significant.All statistical analyses were performed using the "TwoSampleMR" package in R software version 4.3.0.

Instrumental variables
Forty-six SNPs that were strongly associated with multiple sclerosis (P < 5 × 10 −8 ) without chain imbalance (r 2 < 0.001, kb = 10,000) were screened in the present study.Forty-six SNPs were left by taking the intersection with SNPs in the pooled data from the GWAS for spinal stenosis, and also by eliminating SNPs that were directly associated with the outcome metrics.
In our study, the F values of each SNP were all >10, indicating no weak instrumental variables (see Table 1 for details).We searched the human genotype-phenotype association database and found no potentially relevant risk factor SNPs.

Causal relationship between multiple sclerosis and spinal stenosis
By MR analysis, the results of IVW showed a positive correlation between multiple sclerosis and spinal stenosis, and the differences were all statistically significant, i.e., there was a causal relationship between multiple sclerosis and spinal stenosis.IVW:OR = 1.05, 95% CI = 1.01-1.08,P = .016;weighted median:OR = 1.00, 95% CI = 0.95-1.05,P = .928;MR Egger:OR = 1.02, 95% CI = 0.96-1.09,P = .509(see Table 2 for details).We can see from both the scatter plot (Fig. 1) and the forest plot (Fig. 2) that having MS increases the risk of developing spinal stenosis.

Sensitivity analysis
Heterogeneity was tested using the IVW method (Cochran Q test, P = .143),and the results suggested that there was no heterogeneity.A funnel plot was drawn to show the heterogeneity results, as shown in Figure 3. MR-PRESSO was used to screen for SNPs that could lead to heterogeneity, and the results did not reveal any SNPs that would lead to heterogeneity in the results.The result of Global test by MR-PRESSO suggested that there was no pleiotropy (P = .448).The "leave-one-out" method uses the IVW method by default, and as can be seen in Figure 4, no single SNP will have a large impact on the overall results after eliminating any SNP, indicating that the results are robust.

Discussion
It is known that multiple sclerosis may be an observational risk factor for spinal stenosis, but the causality of this association is unclear.Our MR study aimed to reveal the causal relationship between multiple sclerosis and spinal stenosis.The results showed a causal relationship between multiple sclerosis and the occurrence of spinal stenosis, as demonstrated by the 2-sample MR results, with an OR (95% CI) of 1.05 (1.01-1.08),P = .016.Young et al [14] found that the probability of suffering from spinal stenosis in the population of patients with multiple sclerosis was much higher than in the general population.
The present study confirms the causal relationship between multiple sclerosis and with the occurrence of spinal stenosis from a genetic point of view.The results of this study are consistent with Young's conclusion that multiple sclerosis is a risk factor for the development of spinal stenosis and that having multiple sclerosis increases the incidence of spinal stenosis.
The present study used a Mendelian randomization study rather than a retrospective study, which is susceptible to confounding factors and reverse causation, and therefore the causal inferences obtained are considered to be of limited value.In contrast, Mendelian randomization (MR) analysis is a new epidemiological approach that uses genetic variation as an instrumental variable of exposure to enhance causal inference.This approach reduces the effects caused by confounding factors. [28]t the same time this study has some limitations.Firstly, as all the data are from people of European origin, the results are not representative of a truly random population sample, nor are they applicable to other so races.Secondly, although various sensitivity analyses have been performed in this study to test the hypotheses of the MR study, it is difficult to completely rule out horizontal pleiotropy of instrumental variables.Finally, the current sample size of GWAS data is still not large enough, and more in-depth studies using more GWAS data are needed in the future.

Conclusion
In conclusion, this study used 2-sample MR analysis to analyze and explore the genetic data, and the results showed a causal relationship between multiple sclerosis and the occurrence of spinal stenosis.

Figure 2 .
Figure 2. Forest plot of multiple sclerosis and spinal stenosis.MR = Mendelian randomization.

Table 1
Information on the final screening of multiple sclerosis SNPs from GWAS data (n = 46).

Table 2
MR regression results of the 3 methods.